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Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors

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  • Li, Huajiao
  • Fang, Wei
  • An, Haizhong
  • Gao, Xiangyun
  • Yan, Lili

Abstract

Economic networks in the real world are not homogeneous; therefore, it is important to study economic networks with heterogeneous nodes and edges to simulate a real network more precisely. In this paper, we present an empirical study of the one-mode derivative holding-based network constructed by the two-mode affiliation network of two sets of actors using the data of worldwide listed energy companies and their shareholders. First, we identify the primitive relationship in the two-mode affiliation network of the two sets of actors. Then, we present the method used to construct the derivative network based on the shareholding relationship between two sets of actors and the affiliation relationship between actors and events. After constructing the derivative network, we analyze different topological features on the node level, edge level and entire network level and explain the meanings of the different values of the topological features combining the empirical data. This study is helpful for expanding the usage of complex networks to heterogeneous economic networks. For empirical research on the worldwide listed energy stock market, this study is useful for discovering the inner relationships between the nations and regions from a new perspective.

Suggested Citation

  • Li, Huajiao & Fang, Wei & An, Haizhong & Gao, Xiangyun & Yan, Lili, 2016. "Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 224-232.
    • Handle: RePEc:eee:phsmap:v:449:y:2016:i:c:p:224-232
    DOI: 10.1016/j.physa.2016.01.009
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    References listed on IDEAS

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    Cited by:

    1. Qing Yao & Tim S Evans & Kim Christensen, 2019. "How the network properties of shareholders vary with investor type and country," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-19, August.
    2. Jiang, Meihui & An, Haizhong & Jia, Xiaoliang & Sun, Xiaoqi, 2017. "The influence of global benchmark oil prices on the regional oil spot market in multi-period evolution," Energy, Elsevier, vol. 118(C), pages 742-752.
    3. Arif, Asma & An, Pengli & Qi, Yajie & Li, Huajiao & An, Haizhong & Hussain, Mujahid & Wang, Yanli, 2021. "The influence factors of the national roles in the FDI network: A combined methods of complex networks and Panel Data Analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    4. Zhu, Zhiyun & Dong, Zhiliang & Zhang, Yanxing & Suo, Guibin & Liu, Sen, 2020. "Strategic mineral resource competition: Strategies of the dominator and nondominator," Resources Policy, Elsevier, vol. 69(C).
    5. Qing Yao & Tim Evans & Kim Christensen, 2018. "How the network properties of shareholders vary with investor type and country," Papers 1812.06694, arXiv.org, revised Sep 2019.
    6. Sun, Qingru & Gao, Xiangyun & Wen, Shaobo & Chen, Zhihua & Hao, Xiaoqing, 2018. "The transmission of fluctuation among price indices based on Granger causality network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 36-49.

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